Data Literacy, Architecture, and Governance Are Key to Successful Self-Service BI
Business analysts—tasked with developing reports, doing data discovery and exploration, or developing data science models and applications—have long sought to reduce or eliminate reliance on their IT service providers for data access, prep, and analysis. Self-service business intelligence (SSBI) tools, and the associated analytic data infrastructure (including easy-to-access and use data, self-service data-prep tools, and data catalogs) to support SSBI, rapidly emerged to support this need.
For several years, Dresner Advisory Services has tracked the market trends and best practices in SSBI. In addition to our annual SSBI Market Report, we held a panel discussion at the 2020 Real BI Conference, a webinar, and a Tweetchat to explore the state of SSBI, as well as organization and user successes and challenges with SSBI.
From these sources and other research, we see that SSBI effectiveness and success depends strongly on how well a user can locate and access analytic content. That ability to locate and access analytic content in turn depends highly on data-literacy levels, the analytic data infrastructure architecture used, and governance applied.
1. Organizations consistently identify SSBI among their top technologies and initiatives considered strategic to BI.
2. The primary use case for SSBI is data discovery and exploration.
3. 51 percent of respondents consider it difficult or impossible to locate analytic content relevant to their BI use cases.
4. Organizations that report it easiest to find analytic content also report the highest levels of success in their BI initiatives. Those that consider their BI initiatives as unsuccessful report finding analytic content difficult or impossible at a rate three to four times higher than their counterparts in organizations with successful BI initiatives.
5. Organizations that report moderate or higher levels of data literacy among users also show the fewest instances of finding analytic content either difficult or impossible. At the other end of the spectrum, those that indicate low or very low levels of data literacy among users also report the most instances of finding analytic content either difficult or impossible.
6. Most organizations have more than one SSBI use case and tool—likely requiring a different set of data pipelines and data infrastructure to support each use case.
7. Users’ ability to locate and access analytic content, trust/governance of the content and results, and choices for analytic data infrastructure and workflow pipeline components are challenges that organizations need to address when implementing and investing further in SSBI. Easy-to-use SSBI tools cannot address these challenges.